Senior Data Engineer

Summary

Apple's App Store is the world's largest and most innovative app marketplace, home to over 2 million apps and serving more than half a billion customers every week across all Apple devices. Since the App Store launched in 2008, it has changed how we all live: enabling countless new companies, spawning new industries, and building millions of jobs. We believe we are just getting started. Do you have a strong passion for using data to drive business decisions, generate ideas, and inspire collaborators? We are seeking for a Senior Data Engineer to join our App Store Data team and play an integral role in helping the App Store to improve the experience for users and developers every day, through analytics solutions grounded in privacy. We build the solutions, services, and mission critical analytics that power data-driven innovation for internal stakeholders and external partners.

Description

As a Senior Data Engineer, you will own the design and delivery of highly reliable, privacy-centric data products, including pipelines, analytical outputs and data services, at the App Store scale. You will architect distributed pipelines, build self-service data platforms, and implement GenAI-driven observability to ensure the highest bar of data quality. You will work closely with Apple Services data analytics, data science, on-device engineering, program, product, privacy and other teams.
The ideal candidate combines strong software engineering and data expertise with excellent communication skills, product sensibility and a curiosity about technology.

Preferred Qualifications

Domain expertise in online advertising measurement, including attribution modeling, incrementality testing, conversion measurement, or campaign optimization
Hands-on experience with privacy-enhancing technologies (e.g., differential privacy, federated learning, secure multi-party computation, or on-device intelligence)
Experience building LLM-driven or agentic workflows for automated data operations, such as anomaly detection, pipeline self-healing, or data quality enforcement

Minimum Qualifications

Bachelor's Degree in Computer Science, Engineering, or a related technical field
7+ years of experience architecting and operating production-grade distributed data systems at large scale
Expert programming skills in Scala or Java, proficient in Python and SQL with excellent analytical and problem-solving skills
Hands-on experience in modern big data technologies such as: Spark/Flink, Kafka, Airflow, Iceberg, Trino, Cassandra and Kubernetes
Strong foundational knowledge of data modeling and data warehouse design
Excellent communication skills with a proven track record of leading cross-functional technical initiatives